Triple
T17488613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grandpere Tiger |
E425839
|
entity |
| Predicate | languageAccent |
P68361
|
FINISHED |
| Object | French accent |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: French accent | Statement: [Grandpere Tiger, languageAccent, French accent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageAccent Context triple: [Grandpere Tiger, languageAccent, French accent]
-
A.
pronunciationLanguage
Indicates the language in which the pronunciation of an entity (such as a word or name) is given.
-
B.
speaksWithAccentWhenUsing
chosen
Indicates that an entity consistently uses a particular accent when using a specified language, medium, or communication mode.
-
C.
hasBritishAccent
Indicates that the subject speaks with a British accent.
-
D.
regionalDialect
Indicates that one entity uses or is associated with a dialect specific to a particular geographic region in relation to another entity.
-
E.
isSpokenAs
Indicates that one entity is used as the spoken or verbal form of another entity (e.g., a word, name, or phrase).
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d889dccf7481909264a1844a2e9100 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451d376708190a97804529174eaf2 |
completed | April 19, 2026, 3:53 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f341c88190adabe526d8903b05 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:48 a.m.